[HTML][HTML] Review on smartphone sensing technology for structural health monitoring

H Sarmadi, A Entezami, KV Yuen, B Behkamal - Measurement, 2023 - Elsevier
Sensing is a critical and inevitable sector of structural health monitoring (SHM). Recently,
smartphone sensing technology has become an emerging, affordable, and effective system …

Deep learning for structural health monitoring: Data, algorithms, applications, challenges, and trends

J Jia, Y Li - Sensors, 2023 - mdpi.com
Environmental effects may lead to cracking, stiffness loss, brace damage, and other
damages in bridges, frame structures, buildings, etc. Structural Health Monitoring (SHM) …

Real-time autonomous indoor navigation and vision-based damage assessment of reinforced concrete structures using low-cost nano aerial vehicles

S Tavasoli, X Pan, TY Yang - Journal of Building Engineering, 2023 - Elsevier
This paper presents a novel autonomous inspection framework for low-cost nano aerial
vehicles (NAVs) in indoor assessment scenarios. First, a novel autonomous navigation and …

Autonomous 3D vision‐based bolt loosening assessment using micro aerial vehicles

X Pan, S Tavasoli, TY Yang - Computer‐Aided Civil and …, 2023 - Wiley Online Library
Earlier identification of bolt loosening is crucial to maintain structural integrity and prevent
system‐level collapse. In this study, a novel drone‐based 3D vision methodology has been …

Deep learning‐based segmentation model for permeable concrete meso‐structures

D Chen, Y Li, J Tao, Y Li, S Zhang… - … ‐Aided Civil and …, 2024 - Wiley Online Library
The meso‐structure of pervious concrete significantly influences its overall performance.
Accurately identifying the meso‐structure of pervious concrete is imperative for optimizing …

3D vision-based bolt loosening assessment using photogrammetry, deep neural networks, and 3D point-cloud processing

X Pan, TY Yang - Journal of Building Engineering, 2023 - Elsevier
Structural bolts are essential structural elements. Detection of structural bolt loosening is of
great importance to provide earlier warnings of structural damages and prevent catastrophic …

Self‐training approach for crack detection using synthesized crack images based on conditional generative adversarial network

S Shim - Computer‐Aided Civil and Infrastructure Engineering, 2024 - Wiley Online Library
Urban infrastructure plays a crucial role in determining the quality of life for citizens.
However, given the increasing number of aging infrastructures, regular inspections are …

CR-YOLOv8: Multiscale object detection in traffic sign images

LJ Zhang, JJ Fang, YX Liu, HF Le, ZQ Rao… - IEEE Access, 2023 - ieeexplore.ieee.org
Due to the large-scale changes of different forms of traffic signs and the rapid speed of
vehicles, the detection accuracy and real-time performance of general object detectors are …

Road crack detection interpreting background images by convolutional neural networks and a self‐organizing map

T Yamaguchi, T Mizutani - Computer‐Aided Civil and …, 2024 - Wiley Online Library
The presence of road cracks is an important indicator of damage. Deep learning is a
prevailing method for detecting cracks in road surface images because of its detection …

Self‐supervised representation learning of metro interior noise based on variational autoencoder and deep embedding clustering

Y Wang, H Xiao, Z Zhang, X Guo… - Computer‐Aided Civil …, 2024 - Wiley Online Library
The noise within train is a paradox; while harmful to passenger health, it is useful to
operators as it provides insights into the working status of vehicles and tracks. Recently …